Database Activity Regulation via Rate-Limited Verification
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Solution Overview
Problem
Existing techniques for preventing automated activities by web crawlers, scrapers, and bots often degrade the user experience for legitimate users, as they can be intrusive and consume computational resources, while failing to effectively distinguish between human and automated requests.
Innovation Solution
Implementing a system that sets usage rate limits for database activities based on monitoring periods and confidence intervals, requiring human verification only when attempted usage exceeds these limits, thereby allowing legitimate human activity while constraining automated activity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If existing techniques for preventing automated activity are implemented, then automated activity is reduced, but user experience for legitimate customers deteriorates
Solution Approach 1:
The system applies different treatment to different sources of database activity based on their characteristics. Legitimate user activity is allowed to proceed normally without verification, while suspicious automated activity triggering the rate limit is subjected to human verification. This local differentiation resolves the contradiction by targeting prevention measures only at harmful sources rather than applying them universally.
Solution Approach 2:
A server acts as an intermediary between client devices and the database, monitoring usage rates and selectively requiring human verification. This intermediary layer filters out automated activity while allowing legitimate user activity to pass through without interruption, thus protecting the database without degrading user experience.
2Object-affected harmful factors
If existing techniques for preventing automated activity are implemented, then automated activity is reduced, but computational resources are consumed
Solution Approach 1:
The system implements partial verification by requiring human verification only when usage rates exceed the threshold, rather than verifying all database activities. This selective approach reduces computational resource consumption while still effectively preventing automated activity that exceeds normal usage patterns.
Solution Approach 2:
The system changes the parameter of verification requirement based on the usage rate parameter. When usage exceeds the rate limit, the verification parameter switches from optional to mandatory. This dynamic parameter adjustment optimizes resource usage by applying verification only when necessary to prevent automated abuse.
3Object-affected harmful factors
If usage rate limits are enforced for all users, then automated activity is constrained, but legitimate user activity is impacted
Solution Approach 1:
The system dynamically adjusts the enforcement of usage rate limits based on real-time monitoring of usage patterns. When usage exceeds the rate limit, human verification is triggered; when usage remains within limits, activity proceeds without interruption. This dynamic response constrains automated activity while maintaining productivity for legitimate users.
Solution Approach 2:
The system continuously monitors database usage rates and provides feedback by selectively requiring human verification when thresholds are exceeded. This feedback mechanism allows legitimate user activity to continue uninterrupted while automatically triggering verification for suspicious automated activity, thus resolving the contradiction between constraint and productivity.
Data Source
AI summary
Methods and systems are provided for regulating access to a database by a server. One exemplary method involves the server receiving one or more requests for an activity with respect to the database and determining an attempted usage for the activity over a monitoring period by a source of the requests. When the attempted usage exceeds an allowed usage of the activity for the monitoring period, the server creates an entry in a cache that includes an identifier associated with the source of the one or more requests. Thereafter, the requested activity with respect to the database on behalf of the source may be prevented based on the entry in the cache.